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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement errors during the animal study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Hybrid Ultrasonic TOFD Imaging of Weld Flaws Using Wavelet Transforms and Image Registration

Ultrasonic time of flight diffraction (TOFD) is an effective weld crack inspection technique. Due to the intensity of diffraction wave is rather weak compared with the lateral wave and the bottom echo wave, thus the signal-to-ratio (SNR) of TOFD image is low. A new dichotomous method is comprised of two steps that contains wavelet shrinkage and image registration is proposed in this paper to reduce the noise and improve the resolution of TOFD images as well. In order to evaluate the reliability of our proposed method in this paper, we have established the experiment system, and sampled a number of TOFD data with random distribution of noise characteristics. We adopted one-dimension wavelet transform and two-dimension wavelet transform in the very beginning of the first step of the proposed algorithm respectively. The SNR of the result obtained in this step is improved significantly compared with the classic algorithms. Next, the image registration is applied. After the registered images have been added to form a new one, then it comes to the final result that shows not only the SNR but also the definition of the image is enhanced effectively.

42 ENGINEERING↗
DOE OSTI2019

A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness

The challenge of quantifying uncertainty propagation in real-world systems is rooted in the high-dimensionality of the stochastic input and the frequent lack of explicit knowledge of its probability distribution. Traditional approaches show limitations for such problems, especially when the size of the training data is limited. To address these diculties, we have developed a general framework of constructing surrogate models on spaces of stochastic input with arbitrary probability measure irrespective of the mutual dependencies between individual components of the random inputs and the analytical form. The present Data-driven Sparsity-enhancing Rotation for Arbitrary Randomness (DSRAR) framework includes a data-driven construction of multivariate polynomial basis for arbitrary mutually dependent probability measure and a sparsity enhancement rotation procedure. This sparsity-enhancing rotation method was initially proposed in our previous work [1] for Gaussian density distributions, which may not be feasible for non-Gaussian distributions due to the loss of orthogonality after the rotation. To remedy such diculties, we developed a new data-driven approach to construct orthonormal polynomials for polynomials for arbitrary mutually dependent (amdP) randomness, ensuring the constructed basis maintains the orthogonality/near-orthogonality with respect to the density of the rotated random vector, where directly applying the regular polynomial chaos including arbitrary polynomial chaos (aPC) [2] shows limitations due to the assumption of the mutual independence between the components of the random inputs. The developed DSRAR framework leads to accurate recovery, with only limited training data, of a sparse representation of the target functions. The eectiveness of our method is demonstrated in challenging problems such as PDEs and realistic molecular systems within high-dimensional conformational space (O(10)) where the underlying density is implicitly represented by a large collection of sample data, as well as systems with explicitly given non-Gaussian probabilistic measures.

Lei, Huan↗
DOE OSTI2021

Analysis and prediction of intersection traffic violations using automated enforcement system data

We report that the automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model’s prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

42 ENGINEERING↗
DOE OSTI2022

Generation of Tunable Stochastic Sequences Using the Insulator–Metal Transition

Probabilistic computing is a paradigm in which data are not represented by stable bits, but rather by the probability of a metastable bit to be in a particular state. The development of this technology has been hindered by the availability of hardware capable of generating stochastic and tunable sequences of “1s” and “0s”. The options are currently limited to complex CMOS circuitry and, recently, magnetic tunnel junctions. Here, we demonstrate that metal–insulator transitions can also be used for this purpose. We use an electrical pump/probe protocol and take advantage of the stochastic relaxation dynamics in VO 2 to induce random metallization events. A simple latch circuit converts the metallization sequence into a random stream of 1s and 0s. The resetting pulse in between probes decorrelates successive events, providing a true stochastic digital sequence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Frequency domain analysis of errors in cross-correlations of ambient seismic noise

We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (~35 km) and dense linear array (~20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05–0.2 Hz) near the ocean microseismic peaks.

58 GEOSCIENCES↗
DOE OSTI2015

On a framework for generating PoD curves assisted by numerical simulations

The Probability of Detection (PoD) curve method has emerged as an important tool for the assessment of the performance of NDE techniques, a topic of particular interest to the nuclear industry where inspection qualification is very important. The conventional experimental means of generating PoD curves though, can be expensive, requiring large data sets (covering defects and test conditions), and equipment and operator time. Several methods of achieving faster estimates for PoD curves using physics-based modelling have been developed to address this problem. Numerical modelling techniques are also attractive, especially given the ever-increasing computational power available to scientists today. Here we develop procedures for obtaining PoD curves, assisted by numerical simulation and based on Bayesian statistics. Numerical simulations are performed using Finite Element analysis for factors that are assumed to be independent, random and normally distributed. PoD curves so generated are compared with experiments on austenitic stainless steel (SS) plates with artificially created notches. We examine issues affecting the PoD curve generation process including codes, standards, distribution of defect parameters and the choice of the noise threshold. We also study the assumption of normal distribution for signal response parameters and consider strategies for dealing with data that may be more complex or sparse to justify this. These topics are addressed and illustrated through the example case of generation of PoD curves for pulse-echo ultrasonic inspection of vertical surface-breaking cracks in SS plates.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Inhibition of Notch signaling pathway using γ-secretase inhibitor delivered by a low dose of Triton-X100 in cultured oral cancer cells

Highlights: • A novel method is developed to deliver γ-secretase inhibitor DAPT using a low dose of Triton-X100. • This approach effectively blocks the cleavage of Notch1 receptor. • The elimination of Notch1 intracellular domain from cell nuclei is confirmed. • Notch1 signaling blockade in mRNA level is demonstrated upon applying this delivery system. How to effectively delivering therapeutic agents, including γ-secretase inhibitors (GSIs), into live cells, remains a significant challenge. This study assessed the effect of Notch signaling inhibition by examining levels of the Notch1 intracellular domain (N1ICD) in cultured oral cancer cells analyzed with random stitched images (2D) and 3D visualizations using confocal microscopy and quantitative gene analysis. Substantially, we have developed a novel method to assist the delivery of γ-secretase inhibitor, DAPT, into live cells in the presence of an effective minimum concentration of Triton-X100 (0.001%) without damaging cell activity and membrane integrity assessed with cell proliferation assays. The images obtained in this study showed that DAPT alone could not block the γ-secretase inhibitor despite inhibiting cell growth. Further analysis of quantitative gene expressions of Notch signaling canonical pathway to verify the effectiveness of the novel method for delivering inhibitor into live cells, displayed deregulation of Notch1, Delta-like ligand 1 (DLL1) and hairy and enhancer of split 1 (Hes1). Our data suggest that Notch1/Hes1 signaling pathway is deactivated using DAPT with a low dose of Triton-X100 in this cancer cells. And the finding also suggests that Notch1 could be engaged by DLL1 to promote differentiation in oral cancer cells. Using this approach, we demonstrate that Triton-X100 is a promising and effective permeabilization agent to deliver γ-secretase inhibitor DAPT into live oral epithelial cells. This strategy has the potential to implicate in the treatment of cancer diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Development of tight-binding based GW algorithm and its computational implementation for graphene

Graphene has been a hot subject of research in the last decade as it holds a promise for various applications. One interesting issue is whether or not graphene should be classified into a strongly or weakly correlated system, as the optical properties may change upon several factors, such as the substrate, voltage bias, adatoms, etc. As the Coulomb repulsive interactions among electrons can generate the correlation effects that may modify the single-particle spectra (density of states) and the two-particle spectra (optical conductivity) of graphene, we aim to explore such interactions in this study. The understanding of such correlation effects is important because eventually they play an important role in inducing the effective attractive interactions between electrons and holes that bind them into excitons. We do this study theoretically by developing a GW method implemented on the basis of the tight-binding (TB) model Hamiltonian. Unlike the well-known GW method developed within density functional theory (DFT) framework, our TB-based GW implementation may serve as an alternative technique suitable for systems which Hamiltonian is to be constructed through a tight-binding based or similar models. This study includes theoretical formulation of the Green’s function G, the renormalized interaction function W from random phase approximation (RPA), and the corresponding self energy derived from Feynman diagrams, as well as the development of the algorithm to compute those quantities. As an evaluation of the method, we perform calculations of the density of states and the optical conductivity of graphene, and analyze the results.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

In this paper the performance of total focusing method is compared with the widely used time-reversal MUSIC super resolution technique. The algorithms are tested with simulated and experimental ultrasonic array data, each containing different noise levels. The simulated time domain signals allow the effects of array geometry, frequency, scatterer location, scatterer size, scatterer separation and random noise to be carefully controlled. The performance of the imaging algorithms is evaluated in terms of resolution and sensitivity to random noise. It is shown that for the low noise situation, time-reversal MUSIC provides enhanced lateral resolution when compared to the total focusing method. However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Faster Randomized Dynamical Decoupling

We present a randomized dynamical decoupling (DD) protocol that can substantially improve the performance of any given deterministic DD scheme for suppressing coherent noise by using no more than two additional pulses. Our construction is implemented by probabilistically applying sequences of pulses, which, when combined, effectively eliminate the error terms that scale linearly with the system-environment coupling strength. As a result, we show that a randomized protocol using a few pulses can outperform deterministic DD protocols that require considerably more pulses. Furthermore, we prove that the randomized protocol provides an improvement compared to deterministic DD sequences that aim to reduce the error in the system’s Hilbert space, such as Uhrig DD, which had been previously regarded to be optimal. To rigorously evaluate the performance, we introduce new analytical methods suitable for analyzing higher-order DD protocols that might be of independent interest. Here, we also present numerical simulations confirming the significant advantage of using randomized protocols compared to widely used deterministic protocols.

Quantum algorithms & computation↗
DOE OSTI2021

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

STRUCTURE IN THE 3D GALAXY DISTRIBUTION. II. VOIDS AND WATERSHEDS OF LOCAL MAXIMA AND MINIMA

The major uncertainties in studies of the multi-scale structure of the universe arise not from observational errors but from the variety of legitimate definitions and detection methods for individual structures. To facilitate the study of these methodological dependencies, we have carried out 12 different analyses defining structures in various ways. This has been done in a purely geometrical way by utilizing the HOP algorithm as a unique parameter-free method of assigning groups of galaxies to local density maxima or minima. From three density estimation techniques (smoothing kernels, Bayesian blocks, and self-organizing maps) applied to three data sets (the Sloan Digital Sky Survey Data Release 7, the Millennium simulation, and randomly distributed points) we tabulate information that can be used to construct catalogs of structures connected to local density maxima and minima. We also introduce a void finder that utilizes a method to assemble Delaunay tetrahedra into connected structures and characterizes regions empty of galaxies in the source catalog.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Prospective Preference Assessment of Patients' Willingness to Participate in a Randomized Controlled Trial of Intensity-Modulated Radiotherapy Versus Proton Therapy for Localized Prostate Cancer

Purpose: To investigate patients' willingness to participate (WTP) in a randomized controlled trial (RCT) comparing intensity-modulated radiotherapy (IMRT) with proton beam therapy (PBT) for prostate cancer (PCa). Methods and Materials: We undertook a qualitative research study in which we prospectively enrolled patients with clinically localized PCa. We used purposive sampling to ensure a diverse sample based on age, race, travel distance, and physician. Patients participated in a semi-structured interview in which they reviewed a description of a hypothetical RCT, were asked open-ended and focused follow-up questions regarding their motivations for and concerns about enrollment, and completed a questionnaire assessing characteristics such as demographics and prior knowledge of IMRT or PBT. Patients' stated WTP was assessed using a 6-point Likert scale. Results: Forty-six eligible patients (33 white, 13 black) were enrolled from the practices of eight physicians. We identified 21 factors that impacted patients' WTP, which largely centered on five major themes: altruism/desire to compare treatments, randomization, deference to physician opinion, financial incentives, and time demands/scheduling. Most patients (27 of 46, 59%) stated they would either 'definitely' or 'probably' participate. Seventeen percent (8 of 46) stated they would 'definitely not' or 'probably not' enroll, most of whom (6 of 8) preferred PBT before their physician visit. Conclusions: A substantial proportion of patients indicated high WTP in a RCT comparing IMRT and PBT for PCa.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Mean-field entanglement transitions in random tree tensor networks

Entanglement phase transitions in quantum chaotic systems subject to projective measurements and in random tensor networks have emerged as a new class of critical points separating phases with different entanglement scaling. We propose a mean-field theory of such transitions by studying the entanglement properties of random tree tensor networks. As a function of bond dimension, we find a phase transition separating area-law from logarithmic scaling of the entanglement entropy. Using a mapping onto a replica statistical mechanics model defined on a Cayley tree and the cavity method, we analyze the scaling properties of such transitions. Our approach provides a tractable, mean-field-like example of an entanglement transition. Furthermore, we verify our predictions numerically by computing directly the entanglement of random tree tensor network states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

SU-E-T-573: The Robustness of a Combined Margin Recipe for Uncertainties During Radiotherapy

Purpose: To investigate the variability of a safety margin recipe that combines CTV and PTV margins quadratically, with several tumor, treatment, and user related factors. Methods: Margin recipes were calculated by monte-carlo simulations in 5 steps. 1. A spherical tumor with or without isotropic microscopic was irradiated with a 5 field dose plan2. PTV: Geometric uncertainties were introduced using systematic (Sgeo) and random (sgeo) standard deviations. CTV: Microscopic disease distribution was modelled by semi-gaussian (Smicro) with varying number of islets (Ni)3. For a specific uncertainty set (Sgeo, sgeo, Smicro(Ni)), margins were varied until pre-defined decrease in TCP or dose coverage was fulfilled. 4. First, margin recipes were calculated for each of the three uncertainties separately. CTV and PTV recipes were then combined quadratically to yield a final recipe M(Sgeo, sgeo, Smicro(Ni)).5. The final M was verified by simultaneous simulations of the uncertainties.Now, M has been calculated for various changing parameters like margin criteria, penumbra steepness, islet radio-sensitivity, dose conformity, and number of fractions. We subsequently investigated A: whether the combined recipe still holds in all these situations, and B: what the margin variation was in all these cases. Results: We found that the accuracy of the combined margin recipes remains on average within 1mm for all situations, confirming the correctness of the quadratic addition. Depending on the specific parameter, margin factors could change such that margins change over 50%. Especially margin recipes based on TCP-criteria are more sensitive to more parameters than those based on purely geometric Dmin-criteria. Interestingly, measures taken to minimize treatment field sizes (by e.g. optimizing dose conformity) are counteracted by the requirement of larger margins to get the same tumor coverage. Conclusion: Margin recipes combining geometric and microscopic uncertainties quadratically are accurate under varying circumstances. However margins can change up to 50% for different situations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Calculating beta decay in the deformed self-consistent quasiparticle random phase approximation

We discuss a recent global calculation of beta-decay rates in the self-consistent Skyrme quasiparticle random phase approximation (QRPA), with axially symmetric nuclear deformation treated explicitly. The calculation makes makes use of the finite-amplitude method, first proposed by Nakatsukasa and collaborators, to reduce computation time. The results are comparable in quality to those of several other global QRPA calculations. The QRPA may have reached the limit of its accuracy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗